Scholar
Yashas Annadani
Google Scholar ID: ExgzcVMAAAAJ
Helmholtz AI, TU Munich
Citations & Impact
Citations
529
H-index
8
i10-index
8
Publications
18
Co-authors
15
list available
Publications
Resume (English only)
Academic Achievements
- Published 'Amortized Active Causal Induction with Deep Reinforcement Learning' at NeurIPS 2024
- Published 'BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery' at NeurIPS 2023
- Co-authored 'Trust Your Gradients: Gradient-based Intervention Targeting for Causal Discovery' at NeurIPS 2023
- Published 'Differentiable Multi-Target Causal Bayesian Experimental Design' at ICML 2023
- Co-authored 'Structure by Architecture: Structured Representations without Regularization' at ICLR 2023
- Co-authored 'Interventions, Where and How? Experimental Design for Causal Models at Scale' at NeurIPS 2022
- Presented 'Learning Neural Causal Models with Active Interventions' at NeurIPS WHY-21 workshop in 2021
- Oral presentation of 'Variational Causal Networks: Approximate Bayesian Inference over Causal Structures' at KDD Workshop on Bayesian causal inference in 2021
- Published 'Preserving Semantic Relations for Zero-Shot Learning' at CVPR 2018
